Combining PolSAR, Pol-InSAR and TomoSAR for Snow and Ice Subsurface Characterization

Kurzfassung

Polarimetric and (multi-baseline) interferometric techniques are promising tools to investigate the subsurface properties of glaciers and ice sheets, due to the signal penetration of up to several tens of meters into dry snow, firn, and ice. Two different lines of research were addressed in recent years. The first is based on PolSAR, which provides not only information about the scattering mechanisms, but also has the uniqueness of being sensitive to anisotropic signal propagation in non-scattering layers of snow and firn. The second line of research is related to the use of Pol-InSAR and TomoSAR to retrieve the 3D location of scatterers within the subsurface. So far, the potential of the different SAR techniques was only assessed separately. In the field of PolSAR, modeling efforts have been dedicated to establish a link between co-polarization HH-VV phase differences (CPDs) and the structural properties of snow and firn [1][2]. CPDs have then been interpreted as the result of propagation effects due to the dielectric anisotropy of such materials. In the simplest case of snow-covered terrain, the volume scattering from the snowpack can be neglected and the total backscattered signal can be attributed to the underlying ground. The measured CPD arises then from the radar signal propagation through the entire snow layer and can be used to retrieve snow depth [1]. In the case of firn, i.e. in a glacier scenario, the relation between depth and CPD involves also the vertical distribution of backscattering generated by ice inclusions, such as layers and lenses. These scatterers are distributed along depth and influence the signal propagation in the firn volume. The CPD contributions corresponding to the location of the different scatterers have then to be integrated along depth. Up to now, only a simple constant vertical backscattering distribution was considered [2] to attempt the inversion of firn thickness. In the fields of Pol-InSAR and TomoSAR for the investigation of the subsurface scattering structure of ice sheets, recent studies are mainly concerned with the estimation of the vertical backscatter distribution, either model-based or through tomographic imaging techniques. Pol-InSAR models exploit the dependence of the interferometric volume decorrelation on the vertical distribution of backscattering. By modeling the subsurface as a homogeneous, lossy, and infinitely deep scattering volume, a relation between InSAR coherence magnitudes and the constant extinction coefficient of the microwave signals in the subsurface of ice sheets was established in [3]. This approach approximates the vertical backscattering distribution as an exponential function and allows the estimation of the signal extinction parameter, which is a first, yet simplified, indicator of subsurface properties. Recent improvements in subsurface scattering distribution modeling [4], [5] showed the potential to account for refrozen melt layers and variable extinctions, which could provide geophysical information about melt-refreeze processes and subsurface density. With TomoSAR, the imaging of subsurface features in glaciers [6], and ice sheets [5][7][8] was demonstrated. Depending on the study, the effect of subsurface layers, different ice types, firn bodies, crevasses, and the bed rock was recognized in the tomograms. This verified that the subsurface of glaciers and ice sheets can have a more complex backscattering structure than what is accounted for in current models. SAR tomography plays, therefore, a major role for investigating and improving subsurface scattering modeling of ice sheets. This study will address a promising line for future research, which is the combination of PolSAR and Pol-InSAR/TomoSAR approaches to fully exploit their complementarity and mitigate their weaknesses. As described above, on the one hand, polarimetry is sensitive to the signal propagation in snow and firn and thus to the non-scattering part of the subsurface, but provides no vertical information. On the other hand, Pol-InSAR (models) and TomoSAR allow assessing the 3-D distribution of scatterers in the subsurface, but provide no information on the anisotropic propagation effects of snow and firn. This study will investigate the synergies between the individual methods by integrating the models and algorithms into one common framework. Accordingly, the first step will be an integration of Pol-InSAR/TomoSAR vertical scattering profiles into the depth-integral of the CPD for the estimation of firn thickness with PolSAR. This will resemble a more realistic model setup and is expected to improve the estimation. Furthermore, the added information from the CPDs could act as a regularization when inverting Pol-InSAR models, opening up further potential for subsurface structure estimation. 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